Mathematics for Machine Learning : Linear Regression & Least Square Regression

As we know from the basic maths that if we plot an'X','Y' graph, a linear relationship will always come up with a straight line. The equation of a straight line is written using the y mx b, where m is the slope (Gradient) and b is y-intercept (where the line crosses the Y axis). Once we get the equation of a straight line from 2 points in space in y mx b format, we can use the same equation to predict the points at different values of x which result in a straight line. In this formula, m is the slope and b is y-intercept. Let's take a real world example to demonstrate the usage of linear regression and usage of Least Square Method to reduce the errors Let's take a real world example of the price of agricultural products and how it varies based on the location its sold.